rand - pseudo-random number generator
int RAND_set_rand_engine(ENGINE *engine);
int RAND_bytes(unsigned char *buf, int num);
int RAND_pseudo_bytes(unsigned char *buf, int num);
void RAND_seed(const void *buf, int num);
void RAND_add(const void *buf, int num, int entropy);
int RAND_load_file(const char *file, long max_bytes);
int RAND_write_file(const char *file);
const char *RAND_file_name(char *file, size_t num);
int RAND_egd(const char *path);
void RAND_set_rand_method(const RAND_METHOD *meth);
const RAND_METHOD *RAND_get_rand_method(void);
/* For Win32 only */
int RAND_event(UINT, WPARAM, LPARAM);
Since the introduction of the ENGINE API, the recommended way of controlling
default implementations is by using the ENGINE API functions. The default
, as set by RAND_set_rand_method()
and returned by
, is only used if no ENGINE has been set as the
default "rand" implementation. Hence, these two functions are no
longer the recommened way to control defaults.
If an alternative RAND_METHOD
implementation is being used (either set
directly or as provided by an ENGINE module), then it is entirely responsible
for the generation and management of a cryptographically secure PRNG stream.
The mechanisms described below relate solely to the software PRNG
implementation built in to OpenSSL and used by default.
These functions implement a cryptographically secure pseudo-random number
generator (PRNG). It is used by other library functions for example to
generate random keys, and applications can use it when they need randomness.
A cryptographic PRNG must be seeded with unpredictable data such as mouse
movements or keys pressed at random by the user. This is described in
. Its state can be saved in a seed file (see
) to avoid having to go through the seeding process
whenever the application is started.
describes how to obtain random data from the PRNG.
method implements a PRNG based on a cryptographic hash
The following description of its design is based on the SSLeay documentation:
First up I will state the things I believe I need for a good RNG.
- A good hashing algorithm to mix things up and to convert the RNG 'state'
to random numbers.
- An initial source of random 'state'.
- The state should be very large. If the RNG is being used to generate 4096
bit RSA keys, 2 2048 bit random strings are required (at a minimum). If
your RNG state only has 128 bits, you are obviously limiting the search
space to 128 bits, not 2048. I'm probably getting a little carried away on
this last point but it does indicate that it may not be a bad idea to keep
quite a lot of RNG state. It should be easier to break a cipher than guess
the RNG seed data.
- Any RNG seed data should influence all subsequent random numbers
generated. This implies that any random seed data entered will have an
influence on all subsequent random numbers generated.
- When using data to seed the RNG state, the data used should not be
extractable from the RNG state. I believe this should be a requirement
because one possible source of 'secret' semi random data would be a
private key or a password. This data must not be disclosed by either
subsequent random numbers or a 'core' dump left by a program crash.
- Given the same initial 'state', 2 systems should deviate in their RNG
state (and hence the random numbers generated) over time if at all
- Given the random number output stream, it should not be possible to
determine the RNG state or the next random number.
The algorithm is as follows.
There is global state made up of a 1023 byte buffer (the 'state'), a working
hash value ('md'), and a counter ('count').
Whenever seed data is added, it is inserted into the 'state' as follows.
The input is chopped up into units of 20 bytes (or less for the last block).
Each of these blocks is run through the hash function as follows: The data
passed to the hash function is the current 'md', the same number of bytes from
the 'state' (the location determined by in incremented looping index) as the
current 'block', the new key data 'block', and 'count' (which is incremented
after each use). The result of this is kept in 'md' and also xored into the
'state' at the same locations that were used as input into the hash function.
I believe this system addresses points 1 (hash function; currently SHA-1), 3
(the 'state'), 4 (via the 'md'), 5 (by the use of a hash function and xor).
When bytes are extracted from the RNG, the following process is used. For each
group of 10 bytes (or less), we do the following:
Input into the hash function the local 'md' (which is initialized from the
global 'md' before any bytes are generated), the bytes that are to be
overwritten by the random bytes, and bytes from the 'state' (incrementing
looping index). From this digest output (which is kept in 'md'), the top (up
to) 10 bytes are returned to the caller and the bottom 10 bytes are xored into
Finally, after we have finished 'num' random bytes for the caller, 'count'
(which is incremented) and the local and global 'md' are fed into the hash
function and the results are kept in the global 'md'.
I believe the above addressed points 1 (use of SHA-1), 6 (by hashing into the
'state' the 'old' data from the caller that is about to be overwritten) and 7
(by not using the 10 bytes given to the caller to update the 'state', but they
are used to update 'md').
So of the points raised, only 2 is not addressed (but see RAND_add(3)